Surveillance equipment is oftentimes used to maintain the security of homes and businesses. For example, video cameras may be used to monitor a parking facility entrance and/or transaction location of an office or business. Images of the video camera may be recorded on video tape to provide a record of activity of the surveillance site. The video tapes containing the recorded images may be viewed by security personnel or stored for future use.
To reduce the quantity of video tape recorded images, motion detection and/or image recording systems are generally used to detect changes in the surveillance scene and record the surveillance scene if the changes exceed a predetermined criteria. For example, one system for motion detection and image recording includes generating digital image snapshots of a scene and determining pixel characteristics for each snapshot. The pixel characteristics are then compared from one image to the next image and, if the pixel characteristic differences exceed a predetermined criteria, the snapshot is digitally recorded.
Conventional motion detection and image recording systems, however, suffer several disadvantages. For example, pixel characteristic differences between comparative images may often result in the recording of insignificant scene variations. For example, pixel characteristics may exceed the predetermined pixel differential criteria as a result of lighting variations, such as variable cloud cover, shadows, wind induced motion, and precipitation. Thus, scene variations of little or no interest may be recorded, thereby utilizing limited storage capacity.
Additionally, to reduce the recording of images containing minor variations between image snapshots due to pixel differentiation techniques, conventional motion detection and image recording systems compare consecutive snapshot images to compensate for minor lighting and other pixel characteristic variations. However, comparing consecutive image snapshots also increases the quantity of images retained in memory.